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Geometry as a Confounder When Assessing Ventricular Systolic Function: Comparison Between Ejection Fraction and Strain Antiplatelet therapy in patients with myocardial infarction without obstructive coronary artery disease Cardiovascular Aging and Heart Failure: JACC Review Topic of the Week Myocardial Infarction Risk Stratification With a Single Measurement of High-Sensitivity Troponin I Efficacy and Safety of Low-Dose Colchicine after Myocardial Infarction Cardiac Shock Care Centers: JACC Review Topic of the Week Morphine and Cardiovascular Outcomes Among Patients With Non-ST-Segment Elevation Acute Coronary Syndromes Undergoing Coronary Angiography Proportion and Morphological Features of Restenosis Lesions With Acute Coronary Syndrome in Different Timings of Target Lesion Revascularization After Sirolimus-Eluting Stent Implantation Impact of Coronary Lesion Complexity in Percutaneous Coronary Intervention: One-Year Outcomes From the Large, Multicentre e-Ultimaster Registry Open sesame technique in percutaneous coronary intervention for ST-elevation myocardial infarction

Review ArticleVolume 12, Issue 14, July 2019

JOURNAL:JACC Cardiovasc Interv. Article Link

Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance

P Sardar, JD Abbott, A Kundu et al. Keywords: artificial intelligence; interventional cardiology

ABSTRACT


Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to fundamentally change the practice of medicine. This field, known as “artificial intelligence” (AI), is making significant progress in areas such as automated clinical decision making, medical imaging analysis, and interventional procedures, and has the potential to dramatically influence the practice of interventional cardiology. The unique nature of interventional cardiology makes it an ideal target for the development of AI-based technologies designed to improve real-time clinical decision making, streamline workflow in the catheterization laboratory, and standardize catheter-based procedures through advanced robotics. This review provides an introduction to AI by highlighting its scope, potential applications, and limitations in interventional cardiology.